Short-term Reservoir Operation Research Articles

Hydropower System Operation and the Quality of Short-Term Hydrologic Ensemble Forecasts

Improving the operational effectiveness of hydropower systems is becoming more relevant considering the shift to renewable energy sources and the rising social, financial, and environmental costs associated with the construction of new hydropower facilities. This challenge is interdisciplinary as it involves technical, managerial, and institutional aspects. This paper focuses on a technical aspect, more specifically on the relationship between the quality of short-term ensemble streamflow forecasts and the energy produced by a hydropower system. A secondary objective is to measure the contribution of both the meteorological and structural uncertainties on the energy output. To achieve this, a numerical experiment comprising multiple sets of hydrologic ensemble forecasts of different quality and a suite of reservoir optimization models is developed for a case study in Canada (the hydropower system of the Gatineau River basin). These ensemble forecasts are processed by the short-term reservoir operation model in rolling-horizon mode over a planning period of 6 years. Each day, the short-term optimization model seeks to maximize the energy output over the 14-day forecast lead time considering the expected future value of the system derived from a midterm optimization model. The relationship between hydropower generation and common statistical scores characterizing the ensemble forecasts indicates that although there is a link between the quality of the forecasts and the energy production, it is not a one-to-one causal relationship. Our results also show that the diversity of hydrological models is beneficial to the production of energy, indicating that the diversity of model structures compensates the deficiencies of individuals models and adds value to the forecast.

Water Balance Calculation Based on Hydrodynamics in Reservoir Operation

Reservoir operation plays an important role in reservoir management. In reservoir operation, water balance calculation is a very important step. At present, one of the main challenges is that reservoir inflow cannot be calculated accurately due to jacking of the reservoir, which is produced by a downstream reservoir after the original course of the river has changed. Another reason that reservoir capacity cannot be calculated accurately is due to the influence of dynamic storage capacity. In order to overcome these problems, this report shows that the land zone in front of the dam can be used to calculate reservoir capacity, since it can serve as the boundary for a hydrodynamic model, which can then be used to calculate reservoir inflow to improve accuracy. The Three Gorges Dam was selected as a case study. The results show that compared with the measured data, the RMSE (root mean square error) of the proposed model was 8.5%, whereas the RMSE of the traditional model was 25.9%. The contributions and novelty of this paper are: (a) the proposed model combines a hydrodynamic model with a water balance calculation model to make the calculation of inflow more accurate; (b) the land zone in front of the dam can be used to make the calculation of reservoir capacity more accurate; (c) the proposed method provides a new way to calculate water balance, which can be used for short-term reservoir operation. The application results indicate that this study can provide technical support for the fine operation of reservoirs.

Fuzzy-set-based real-time reservoir operation using genetic algorithm

ABSTRACT A short-term reservoir operation model is developed for irrigation wherein the soil moisture of crops at grids and the reservoir storage are considered as fuzzy sets. The distinguished main features of the model as compared to the former fuzzy short-term reservoir operation model are the consideration of real-coded genetic algorithm and the implementation of the satellite-based gridded soil moisture of crops. The water is released from the reservoir at 10-day time periods by maintaining storage balance and the available water for the irrigation is distributed between the crops at grids by considering ponding depth for paddy, soil moisture continuity and root depth of the crops. The irrigation area is discretized into a number of grids (1º × 1º) to consider the spatial variations of rainfall and soil moisture of the crops. The fuzzy short-term reservoir operation model is optimized by the real-coded genetic algorithm by minimizing soil moisture deficits using forecasted inflow and rainfalls at grids from the present to last periods. The fuzzy short-term reservoir operation model using genetic algorithm performs better as compared to the conceptual reservoir operation policy and is faster than the short-term reservoir operation model using dynamic programming.

Exploring synergistic benefits of Water-Food-Energy Nexus through multi-objective reservoir optimization schemes

This study proposed a holistic three-fold scheme that synergistically optimizes the benefits of the Water-Food-Energy (WFE) Nexus by integrating the short/long-term joint operation of a multi-objective reservoir with irrigation ponds in response to urbanization. The three-fold scheme was implemented step by step: (1) optimizing short-term (daily scale) reservoir operation for maximizing hydropower output and final reservoir storage during typhoon seasons; (2) simulating long-term (ten-day scale) water shortage rates in consideration of the availability of irrigation ponds for both agricultural and public sectors during non-typhoon seasons; and (3) promoting the synergistic benefits of the WFE Nexus in a year-round perspective by integrating the short-term optimization and long-term simulation of reservoir operations. The pivotal Shihmen Reservoir and 745 irrigation ponds located in Taoyuan City of Taiwan together with the surrounding urban areas formed the study case. The results indicated that the optimal short-term reservoir operation obtained from the non-dominated sorting genetic algorithm II (NSGA-II) could largely increase hydropower output but just slightly affected water supply. The simulation results of the reservoir coupled with irrigation ponds indicated that such joint operation could significantly reduce agricultural and public water shortage rates by 22.2% and 23.7% in average, respectively, as compared to those of reservoir operation excluding irrigation ponds. The results of year-round short/long-term joint operation showed that water shortage rates could be reduced by 10% at most, the food production rate could be increased by up to 47%, and the hydropower benefit could increase up to 9.33 million USD per year, respectively, in a wet year. Consequently, the proposed methodology could be a viable approach to promoting the synergistic benefits of the WFE Nexus, and the results provided unique insights for stakeholders and policymakers to pursue sustainable urban development plans.

Incorporating Filters in Random Search Algorithms for the Hourly Operation of a Multireservoir System

AbstractOptimization of short-term reservoir operation normally involves ramping constraints of outflows and water elevations at short time steps (e.g., hourly). Random search algorithms, such as g...

Multi-objective reservoir operation during flood season considering spillway optimization

Flood control and hydropower generation are two main functions of Three Gorges Reservoir (TGR) in China. In this study, a multi-objective operation model for TGR considering these two functions was developed. Since the optimal results of reservoir operation are mostly in the form of gross outflow which is hardly used to directly guide reservoir operation, the optimization of spillways operation was taken into account. For observed historical flood hydrographs and design flood hydrographs, the progressive optimality algorithm (POA) was employed to determine the optimal operation of spillways. For the real-time reservoir operation, a smooth support vector machine (SSVM) model was applied to abstract the optimal operation rules which consider the order and the number of spillways put into use. Results demonstrate that the use of different spillways has a significant impact on reservoir operation. Therefore, it is necessary to consider the order and number of spillways that should be used. Instead of optimizing outflow, direct optimization of the order and number of spillways can yield most reasonable results. The SSVM model simulates the relationship among inflow, water level and outflow satisfactorily and can be used for real-time or short term reservoir operation. Application of the SSVM model can also reduce flood risk and increase hydropower generation during the flood season.

Water quality projection in the Geum River basin in Korea to support integrated basin-wide water resources management

When establishing long- and short-term reservoir operation to support integrated water resources management, reservoir operation emphasizes not only water quantity but also water quality downstream of the reservoir. This study proposes a water quality projection scheme in the Geum River basin based on the pollutant loadings of biochemical oxygen demand, total nitrogen (TN), and total phosphorus (TP) combining with a long-term hydrologic simulation model. In the Geum River basin in Korea, two multipurpose dams, Daechung and Yongdam reservoirs, exist. Downstream of the Daechung reservoir is especially subject to the pollutant loadings released from the metropolitan cities which contribute to water quality degradation in the main stream of the Geum River. To identify the hydrologic cycle in the Geum River basin, long-term hydrologic simulation models have been employed and calibrated with two control points from 1983 to 2008. Water quality simulation based on the flow rates and pollutant loadings estimated in the Geum River basin shows a good agreement with observed ones along the main stream of the Geum River. As a result, the combination of water quality and the hydrologic simulation model provides systematic approach to project water quality downstream of the reservoir and to support reservoir operation in determination of discharge release considering downstream water quality.

Optimal Short-term Reservoir Operation with Integrated Long-term Goals

A methodology to incorporate long-term goals within the short-term reservoir operation optimization model is proposed. Two conflicting objectives for the management of hydropower generation in two different power plants are incorporated. A chance-constrained optimization model is used to derive long-term (annual) operation strategies. With the time horizon of operation for the short-term optimization model kept equal to a single time-step of the long-term optimization model, the optimum end storages derived from the long-term model are incorporated as constraints (storage lower bounds) within the short-term model. The long-term benefits accrued from such an operation model are illustrated for a small reservoir, in South India. The solutions are compared with the historic operation. These are also compared with the solutions of a short-term optimal operation model ignoring long-term goals. The optimization model is solved using a multi-objective genetic algorithm.

Optimization–simulation for short-term reservoir operation under flooding conditions

The problem of optimal operation of river–reservoir systems under flooding conditions is formulated in this study as a combination of particle swarm optimization (PSO) algorithm and a simulation model of river flood routing. Both hydrologic (Muskingum and Muskingum-Cunge) and hydraulic (solving Saint-Venant equations) flow routing methods are linked to the PSO algorithm with the objective function of minimizing flood damage in downstream areas. The Preissmann method is used to numerically solve the continuity and momentum equations. The developed optimization–simulation models were first tested in the case study of flood control operation of Bishop Dam, a benchmark problem in HEC-5 software. The models' performance was verified through their ability to reduce peak discharge at downstream control points compared to that resulting from applying gate regulation curve (GRC) operation policies available in HEC-5. Then the PSO-Venant model was used in the river–reservoir system of Upper Gotvand dam, a real case study in south-west Iran. Results show the significance of the model in determining optimal reservoir releases and minimizing flood damages.

Integrating Long- and Short-Term Reservoir Operation Models via Stochastic and Deterministic Optimization: Case Study in Japan

Real-time reservoir operation models carried out under short operating horizons have no information about the seasonal changes in streamflow. The overall operation may improve provided that long-term information can be incorporated into the short-term process. This paper proposes a procedure that attempts to do such incorporation by means of stochastic and deterministic optimization. Long-term (monthly) and short-term (daily) reservoir inflow forecasts are assumed to be uncertain and reliable, respectively. The idea is to first solve a monthly operation model by an explicit stochastic programming approach and then use its information to guide the daily operation, which is solved by deterministic optimization. The monthly information will decide whether hedging should start being implemented during the daily operation in order to mitigate a potential future shortage. This stochastic-deterministic procedure is applied to a case study in Japan and the results show that it provides operating rules relatively ...

Optimal reservoir operation for irrigation of multiple crops using elitist-mutated particle swarm optimization

To achieve social and economic sustainability in arid and semi-arid areas under water scarce situations, it is vital to promote efficient use of water through improved management of water resources. This paper presents a swarm optimization based solution to a detailed operational model for short-term reservoir operation for irrigation of multiple crops. The model integrates the dynamics associated with the water released from a reservoir to the actual water utilized by crops at farm level. It takes into account the nonlinear relationship of root growth, soil heterogeneity, soil moisture dynamics for multiple crops, yield response to water deficit at various growth stages of the crops and economic benefits from the crops. As the developed model is a nonlinear one, it is solved using a novel global optimization technique, namely elitist-mutation particle swarm optimization (EMPSO). The model's applicability is demonstrated through a case study of Malaprabha Reservoir system in Southern India. The performance of the model is examined for different water deficit conditions and the sensitivity of the crop yield is analysed for water shortage at various growth stages. Also, the consideration of economic benefits in the objective function and its effect on the water allocation decisions for multiple crops are studied. Consequently, the output from the model includes initial storages, releases, overflows and evaporation losses for each 10-day period on the reservoir side; and allocation of water, actual evapotranspiration and initial soil moisture for each crop for each 10-day period on the field side, thus facilitating decision making for optimal utilization of the available water resources.

A short-term reservoir operation model for multicrop irrigation

An integrated model is developed for short-term yearly reservoir operation for irrigation of multiple crops. The model optimizes a measure of annual crop production, starting from the current period in real time. Reservoir storage at the beginning of a period, inflow during the previous period, crop soil moisture values and crop production already achieved up to the beginning of the period are used as inputs to the model. The solution specifies the reservoir release and optimal irrigation allocations to individual crops during an intra-seasonal period. The model overcomes some of the limitations of an earlier model developed by Mujumdar & Ramesh (1997) by replacing the two dynamic programming (DP) formulations with a single linear programming (LP) formulation. Application of the model is studied through a case study in India.

Risk-based parameter selection for short-term reservoir operation

A methodology has been developed to determine the optimal operating horizon for short-term reservoir operation. The modelling procedure includes: (1) an adaptive forecasting algorithm; (2) a real-time reservoir operation model; (3) a multiobjective compromise programming algorithm. The compromise programming algorithm utilizes a multiobjective compromise between the conflicting objectives of hydrologic forecast reliability and reservoir operation penalties. The algorithm requires predetermined weights defining the relative importance of the two objectives. This paper presents a risk-based methodology developed to help a decision maker in selecting the appropriate weights. Reliability, vulnerability, and resiliency are used as three risk-based criteria for assisting in selection of the weights. The methodology is presented in the form of a rule-based system designed to aid the user in the selection process. The methodology is illustrated through an application of the technique to the operation of Green Reservoir in Kentucky. The reservoir model is implemented for four different historical periods and its performance in terms of total penalties, reliability, vulnerability, and resiliency is presented as a function of the multi-objective weighting parameters. The rule-based expert system is then used for deriving recommendations regarding the selection of appropriate weights. The paper also discusses the rule-based expert system development tool, used in this research.